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Updated: May 12, 2026

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CacPred:用于TF-DNA结合预测的级联卷积神经网络.

Shuangquan Zhang1,2, Anjun Ma3, Xuping Xie2

  • 1School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.

BMC genomics
|March 19, 2025
PubMed
概括

一个新的模型,CacPred,增强了转录因子-DNA结合预测的准确性. 这种深度学习方法通过有效地学习序列特征,优于ChIP-seq和ChIP-nexus数据集的现有方法.

关键词:
在 ChIP-seqq.深度学习是一种深度学习.预测TF-DNA结合的结合转录因子是一种转录因子.

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Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
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